diff --git a/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.cc b/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.cc index b50b4f37caecd8d8d5c393ee3a5c5b76c1f406be..fd8b55a6b7deb9bf4685b27f8849a49ab77f64e9 100644 --- a/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.cc +++ b/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.cc @@ -18,6 +18,7 @@ #include #include #include "paddle/fluid/framework/lod_tensor.h" +#include "paddle/fluid/framework/op_version_registry.h" #include "paddle/fluid/operators/math/cpu_vec.h" #include "paddle/fluid/platform/enforce.h" @@ -225,3 +226,14 @@ REGISTER_PASS(conv_affine_channel_fuse_pass, paddle::framework::ir::ConvAffineChannelFusePass); REGISTER_PASS(conv_eltwiseadd_affine_channel_fuse_pass, paddle::framework::ir::ConvEltwiseAddAffineChannelFusePass); +REGISTER_PASS_CAPABILITY(conv_affine_channel_fuse_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("conv2d", 0) + .EQ("affine_channel", 0)); +REGISTER_PASS_CAPABILITY(conv_eltwiseadd_affine_channel_fuse_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("conv2d", 0) + .EQ("elementwise_add", 0) + .EQ("affine_channel", 0)); diff --git a/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc b/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc index 9d3e0806ac79d838765ca5a4bbf61d0f67ab6ed5..fb787e08814429781bf64efda2f1eb915f185f63 100644 --- a/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc +++ b/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc @@ -18,6 +18,7 @@ #include #include #include "paddle/fluid/framework/lod_tensor.h" +#include "paddle/fluid/framework/op_version_registry.h" #include "paddle/fluid/operators/math/cpu_vec.h" #include "paddle/fluid/platform/enforce.h" @@ -372,3 +373,14 @@ REGISTER_PASS(depthwise_conv_bn_fuse_pass, paddle::framework::ir::DepthwiseConvBNFusePass); REGISTER_PASS(depthwise_conv_eltwiseadd_bn_fuse_pass, paddle::framework::ir::DepthwiseConvEltwiseAddBNFusePass); +REGISTER_PASS_CAPABILITY(conv_bn_fuse_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("conv2d", 0) + .EQ("batch_norm", 0)); +REGISTER_PASS_CAPABILITY(conv_eltwiseadd_bn_fuse_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("conv2d", 0) + .EQ("elementwise_add", 0) + .EQ("batch_norm", 0)); diff --git a/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.cc b/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.cc index 2396a7f3c4f84f70c2f350e2121c4044c56b141a..23f794c11c239225b31cea8a7e7f11f576c87081 100644 --- a/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.cc +++ b/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.cc @@ -18,6 +18,7 @@ limitations under the License. */ #include #include #include "paddle/fluid/framework/lod_tensor.h" +#include "paddle/fluid/framework/op_version_registry.h" #define MAX_NUM_FC 10 @@ -174,6 +175,10 @@ void BuildRepeatedFCReluPattern(PDPattern* pattern, if (x->outputs.size() <= 0 || x->inputs.size() <= 0U) { return false; } + if (x->IsVar() && x->Var() && x->Var()->GetShape().size() > 2) { + LOG(WARNING) << "repeated fc relu only supports input dims = 2"; + return false; + } int fc_idx = FindFCIdx(x); if (fc_idx < 0) { return false; @@ -384,3 +389,8 @@ void RepeatedFCReluFusePass::ApplyImpl(ir::Graph* graph) const { REGISTER_PASS(repeated_fc_relu_fuse_pass, paddle::framework::ir::RepeatedFCReluFusePass); +REGISTER_PASS_CAPABILITY(repeated_fc_relu_fuse_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("fc", 0) + .EQ("relu", 0)); diff --git a/paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc b/paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc index d9a65e71592ff464a2e6beaa2219a39103f6cae1..74ba0093a17beb5d30cd0234faf948d8a7dd620d 100644 --- a/paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc +++ b/paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc @@ -16,6 +16,7 @@ #include "paddle/fluid/framework/ir/graph_viz_pass.h" #include "paddle/fluid/framework/ir/shuffle_channel_detect_pass.h" +#include "paddle/fluid/framework/op_version_registry.h" namespace paddle { namespace framework { @@ -34,6 +35,8 @@ void ShuffleChannelDetectPass::ApplyImpl(ir::Graph* graph) const { const std::string pattern_name = "shufflechannel_pattern"; FusePassBase::Init(pattern_name, graph); + LOG(WARNING) << "There is fluid.layers.shuffle_channel API already, you can " + "use it instead of (reshape + transpose +reshape)"; GraphPatternDetector gpd; auto* x = gpd.mutable_pattern() ->NewNode("x") @@ -93,3 +96,8 @@ void ShuffleChannelDetectPass::ApplyImpl(ir::Graph* graph) const { REGISTER_PASS(shuffle_channel_detect_pass, paddle::framework::ir::ShuffleChannelDetectPass); +REGISTER_PASS_CAPABILITY(shuffle_channel_detect_pass) + .AddCombination( + paddle::framework::compatible::OpVersionComparatorCombination() + .EQ("reshape2", 0) + .EQ("transpose2", 0)); diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_conv_affine_channel_fuse_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_conv_affine_channel_fuse_pass.py new file mode 100644 index 0000000000000000000000000000000000000000..ec0bd52e9261017335f0bf424d32f26d4c465029 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_conv_affine_channel_fuse_pass.py @@ -0,0 +1,228 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from inference_pass_test import InferencePassTest +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid.core import PassVersionChecker + + +class ConvAffineChannelFusePassExplicitPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding=[1, 1, 1, 1], + bias_attr=False, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible('conv_affine_channel_fuse_pass')) + + +class ConvAffineChannelFusePassValidPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding='VALID', + bias_attr=False, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible('conv_affine_channel_fuse_pass')) + + +class ConvAffineChannelFusePassSamePaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding='SAME', + bias_attr=False, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible('conv_affine_channel_fuse_pass')) + + +class ConvEltwiseAddAffineChannelFusePassExplicitPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + param_attr = fluid.ParamAttr( + initializer=fluid.initializer.Xavier(uniform=False), + learning_rate=0.001) + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding=[1, 1, 1, 1], + bias_attr=param_attr, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible( + 'conv_eltwiseadd_affine_channel_fuse_pass')) + + +class ConvEltwiseAddAffineChannelFusePassValidPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + param_attr = fluid.ParamAttr( + initializer=fluid.initializer.Xavier(uniform=False), + learning_rate=0.001) + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding='VALID', + bias_attr=param_attr, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible( + 'conv_eltwiseadd_affine_channel_fuse_pass')) + + +class ConvEltwiseAddAffineChannelFusePassSamePaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + param_attr = fluid.ParamAttr( + initializer=fluid.initializer.Xavier(uniform=False), + learning_rate=0.001) + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + groups=3, + padding='Same', + bias_attr=param_attr, + act=None) + input_scale = fluid.layers.create_parameter( + shape=[3], dtype="float32") + input_bias = fluid.layers.create_parameter( + shape=[3], dtype="float32") + ac_out = fluid.layers.affine_channel( + x=conv_out, scale=input_scale, bias=input_bias) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [ac_out] + + def test_check_output(self): + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible( + 'conv_eltwiseadd_affine_channel_fuse_pass')) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_conv_bn_fuse_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_conv_bn_fuse_pass.py new file mode 100644 index 0000000000000000000000000000000000000000..ffe177e59d86e4451b3da1e40fd62e1d398b03b2 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_conv_bn_fuse_pass.py @@ -0,0 +1,177 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from inference_pass_test import InferencePassTest +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid.core import PassVersionChecker + + +class ConvBnFusePassExplicitPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding=[1, 1, 1, 1], + bias_attr=False, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue(PassVersionChecker.IsCompatible('conv_bn_fuse_pass')) + + +class ConvBnFusePassValidPaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding='VALID', + bias_attr=False, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue(PassVersionChecker.IsCompatible('conv_bn_fuse_pass')) + + +class ConvBnFusePassSamePaddingTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding='SAME', + bias_attr=False, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue(PassVersionChecker.IsCompatible('conv_bn_fuse_pass')) + + +class ConvEltwiseAddBnFuseExplicitPaddingPass(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding=[1, 1, 1, 1], + bias_attr=None, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue( + PassVersionChecker.IsCompatible('conv_eltwiseadd_bn_fuse_pass')) + + +class ConvEltwiseAddBnFuseValidPaddingPass(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding='VALID', + bias_attr=None, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue( + PassVersionChecker.IsCompatible('conv_eltwiseadd_bn_fuse_pass')) + + +class ConvEltwiseAddBnFuseSamePaddingPass(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + conv_out = fluid.layers.conv2d( + input=data, + num_filters=6, + filter_size=6, + groups=3, + padding='SAME', + bias_attr=None, + act=None) + bn_out = fluid.layers.batch_norm(conv_out, is_test=True) + + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [bn_out] + + def test_check_output(self): + self.check_output() + self.assertTrue( + PassVersionChecker.IsCompatible('conv_eltwiseadd_bn_fuse_pass')) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_repeated_fc_relu_fuse_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_repeated_fc_relu_fuse_pass.py new file mode 100644 index 0000000000000000000000000000000000000000..c78884480dab38446a20c456aed060eff847a9ed --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_repeated_fc_relu_fuse_pass.py @@ -0,0 +1,94 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from inference_pass_test import InferencePassTest +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid.core import PassVersionChecker + + +class RepeatedFcReluFusePass3Test(InferencePassTest): + def setUp(self): + fc_num = 3 + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + param_attr = fluid.ParamAttr( + initializer=fluid.initializer.Xavier(uniform=False), + learning_rate=0.001) + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + bias_attr=param_attr, + act=None) + fc_outs = [] + fc_outs.append( + fluid.layers.fc(input=[conv_out], act="relu", size=1000)) + for i in range(1, fc_num): + fc_outs.append( + fluid.layers.fc( + input=[fc_outs[i - 1]], act="relu", size=1000)) + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [fc_outs[fc_num - 1]] + + def test_check_output(self): + use_gpu = False + self.check_output_with_option(use_gpu) + + self.assertTrue( + PassVersionChecker.IsCompatible('repeated_fc_relu_fuse_pass')) + + +class RepeatedFcReluFusePass9Test(InferencePassTest): + def setUp(self): + fc_num = 9 + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 3, 64, 64], dtype="float32") + param_attr = fluid.ParamAttr( + initializer=fluid.initializer.Xavier(uniform=False), + learning_rate=0.001) + conv_out = fluid.layers.conv2d( + input=data, + num_filters=3, + filter_size=3, + bias_attr=param_attr, + act=None) + fc_outs = [] + fc_outs.append( + fluid.layers.fc(input=[conv_out], act="relu", size=1000)) + for i in range(1, fc_num): + fc_outs.append( + fluid.layers.fc( + input=[fc_outs[i - 1]], act="relu", size=1000)) + self.feeds = { + "data": np.random.random([1, 3, 64, 64]).astype("float32"), + } + self.fetch_list = [fc_outs[fc_num - 1]] + + def test_check_output(self): + use_gpu = False + self.check_output_with_option(use_gpu) + + self.assertTrue( + PassVersionChecker.IsCompatible('repeated_fc_relu_fuse_pass')) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_trt_shuffle_channel_detect_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_shuffle_channel_detect_pass.py new file mode 100644 index 0000000000000000000000000000000000000000..e9c304496afcc694e47924b9cf0fbd168d08c665 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_shuffle_channel_detect_pass.py @@ -0,0 +1,51 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from inference_pass_test import InferencePassTest +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid.core import PassVersionChecker +from paddle.fluid.core import AnalysisConfig + + +class ShuffleChannelFuseTRTPassTest(InferencePassTest): + def setUp(self): + with fluid.program_guard(self.main_program, self.startup_program): + data = fluid.data( + name="data", shape=[-1, 6, 64, 64], dtype="float32") + reshape1 = fluid.layers.reshape(x=data, shape=[-1, 2, 3, 64, 64]) + trans = fluid.layers.transpose(x=reshape1, perm=[0, 2, 1, 3, 4]) + reshape2 = fluid.layers.reshape(x=trans, shape=[-1, 6, 64, 64]) + out = fluid.layers.batch_norm(reshape2, is_test=True) + + self.feeds = { + "data": np.random.random([1, 6, 64, 64]).astype("float32"), + } + self.enable_trt = True + self.trt_parameters = ShuffleChannelFuseTRTPassTest.TensorRTParam( + 1 << 30, 32, 1, AnalysisConfig.Precision.Float32, False, False) + self.fetch_list = [out] + + def test_check_output(self): + + self.check_output() + + self.assertTrue( + PassVersionChecker.IsCompatible('shuffle_channel_detect_pass')) + + +if __name__ == "__main__": + unittest.main()